Photogrammetric 3D (three-dimensional) reconstruction is a computing technique that enables the automated creation of 3D models of real-world objects using information derived from 2D (two-dimensional) images of those objects. This technique is used in fields such as architectural design, video game development, visual effects production, virtual reality, augmented reality, and so on to generate 3D object models in a manner that is less time-consuming and potentially more precise than manual modeling.
In a conventional photogrammetric 3D reconstruction workflow, an individual (i.e., camera operator) first captures, using one or more cameras, a series of photographs or video frames of a target object or group of objects to be reconstructed with the goal of documenting all exterior surfaces of the target object(s). This process is sometimes referred to as “scanning” the target object(s). Once the scanning is complete, a reconstruction program takes the captured images as input, detects the objects that appear in the images, extracts 3D features of the detected objects, and generates 3D models of the objects based on the extracted features.
One issue with the conventional workflow described above is that, in many cases, the camera(s) used by the camera operator to scan the target object(s) will capture other objects and environmental details which the operator has no interest in reconstructing. For example, if the target object is a model car resting on a table, as part of the scanning process the camera(s) may also capture the table itself, chairs around the table, a wall clock behind the table, and so on. In this example, the camera operator does not want to reconstruct these other objects; he/she is only interested in the model car. However, because they appear in the captured images (perhaps on the image peripheries or in the background), the reconstruction program will nevertheless detect these other objects and create 3D models for them. This increases the amount of compute resources and time needed to carry out the reconstruction process and, in implementations where the precision of reconstruction is constrained according to the overall size of the space being reconstructed, can result in less detail on the 3D model of the target object.